ArticleJournal of registry management2025
Workload and Staffing Study of Hospital Cancer Registries.
Article in Journal of registry management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Modernizing Registry Operations: Implementing File*Pro Automation with Groovy Scripting to Streamline Data Processing in Missouri.Journal of registry management · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of the workload and staffing study of hospital cancer registries conducted in 2024 was to update previous studies of workload and staffing guidelines. The population studied was composed of hospital cancer registries. Potential respondents for this study were hospital registry leads identified in the National Cancer Registrars Association (NCRA) membership database and their cancer registry staff. An online survey was sent to lead registrars along with directions for forwarding a separate cancer registrar survey to their staff. Postsurvey interviews were conducted with 11 experts in the field to review findings and discuss the future of the cancer registry workforce. There were 237 responses to the registry lead survey (RLS) and 290 responses to the cancer registrar survey (CRS). Results indicated a 22% increase in the mean budgeted full-time equivalents (FTEs) from 2019 in 2022; yet filled FTEs decreased slightly from 2019 to 2022. Registry leads reported that nearly half of their staff need additional training in data analysis and were very concerned about recruiting qualified staff, providing adequate compensation, and funding additional positions. Caseload continued to be the main predictor of staffing needs, as in the previous study. In staffing models, we found that for single-institution registries, for every 1,000 cases, staffing should increase by 1.8 to 2.1 FTEs. For multi-institution registries, staffing should increase by 1.6 to 1.9 FTEs for every 1,000 cases. Postsurvey interviewees were concerned about industry-wide vacancies and worker burnout. They mentioned contributing factors such as low wages, lack of recognition, isolated work, the lack of credentialed registrars, and pending retirements. They stressed that technological innovations and automation will not eliminate the registrar's role but will change it. These changes in registrar work may create more specialization in the role such as in data analytics and acting on real-time data and reporting. These changes may also create new career paths that would attract future students and workers to the cancer registry profession. Findings from this study may be useful for hospital registries to benchmark their own workload and staffing and to cancer registry organization leaders in planning for the future.
Indexed as
Identifiers
40656552PMC12244491What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.